Token Classification
Transformers
Safetensors
English
bert
named-entity-recognition
biomedical-nlp
anatomical-entity-recognition
medical-terminology
anatomy
healthcare
Instructions to use OpenMed/OpenMed-NER-AnatomyDetect-PubMed-335M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenMed/OpenMed-NER-AnatomyDetect-PubMed-335M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="OpenMed/OpenMed-NER-AnatomyDetect-PubMed-335M")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("OpenMed/OpenMed-NER-AnatomyDetect-PubMed-335M") model = AutoModelForTokenClassification.from_pretrained("OpenMed/OpenMed-NER-AnatomyDetect-PubMed-335M", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "eval_accuracy": 0.9850553845344279, | |
| "eval_f1": 0.9062679700977573, | |
| "eval_loss": 0.3283041715621948, | |
| "eval_precision": 0.8995433789954338, | |
| "eval_recall": 0.9130938586326767 | |
| } |